Transform a 'glm' object into a flextable

produce a flextable describing a generalized linear model produced by function glm.

You can remove significance stars by setting options options(show.signif.stars = FALSE).

Usage

# S3 method for glm
as_flextable(x, ...)

Arguments

x

glm model

...

unused argument

See also

Other as_flextable methods: as_flextable.data.frame(), as_flextable.gam(), as_flextable.grouped_data(), as_flextable.htest(), as_flextable.kmeans(), as_flextable.lm(), as_flextable.merMod(), as_flextable.pam(), as_flextable.summarizor(), as_flextable.table(), as_flextable.tabular(), as_flextable.tabulator(), as_flextable.xtable(), as_flextable()

Examples

if (require("broom")) {
  dat <- attitude
  dat$high.rating <- (dat$rating > 70)
  probit.model <- glm(high.rating ~ learning + critical +
    advance, data = dat, family = binomial(link = "probit"))
  ft <- as_flextable(probit.model)
  ft
}
#> Loading required package: broom
Estimate
Standard Error
z value
Pr(>|z|)
(Intercept)
-7.476
3.570
-2.094
0.0362
  *
learning
0.164
0.053
3.079
0.0021
 **
critical
-0.001
0.044
-0.013
0.9896
   
advance
-0.062
0.042
-1.472
0.1410
   
Signif. codes: 0 <= '***' < 0.001 < '**' < 0.01 < '*' < 0.05
 
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 38.19 on 29 degrees of freedom
Residual deviance: 18.17 on 26 degrees of freedom